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As the prominent philosopher Jerry, Kaplan puts it “Viewpoint Artificial Intelligence Think Again” (Jerry, 2017). The purpose is that we need to use more hand-working and we do not need Artificial Intelligence replace our brain. Firstly, Social and cultural conventions are an often-neglected aspect of intelligent-machine development. (1) The DOMINANT PUBLIC narrative about artificial intelligence is that we are building increasingly intelligent ma- chines that will ultimately surpass human capabilities, steal our jobs, possibly even escape human control and kill us all. This misguided perception, not widely shared by AI researchers, runs a significant risk of delaying or derailing practical applications and influencing public policy in counterproductive ways. (1) Secondly, Machines don’t have minds, and there is precious little evidence to suggest they ever will. (2) Finally, So the robots are certainly coming, but not in the way most people think. So the robots are certainly coming, but not quite in the way most people think. Concerns that they are going to obsolete us, rise up, and take over, are misguided at best. Worrying about super intelligent machines dis- tracts us from the very real obstacles we will face as increasingly capable machines become more intricately intertwined with our lives and be- gin to share our physical and public spaces. (3)

David himself writes, “CAN INTELLIGENT MACHINES IN THE WORKFORCE LEAD TO A NET GAIN IN THE NUMBER OF JOBS” (David,2016) ? The purpose is that how to choose a job in Artificial Intelligence times. We can meet kinds of problem in the future. The first is that Innovation for jobs and growth. Innovative firms are more competitive, able to capture increased market share and more likely to increase employment than their competitors. Over the period 2006-2011, 1.4 million new jobs were created by firms aged less than three years old. Employment in mature businesses, in contrast, fell 400,000(1). The second is that Jobs of the future. A recent report sponsored by the National Broadband Network (NBN) and the Regional Australia Institute makes the case that by 2030 fully half of Australians will need advanced IT skills, in addition to having well- developed soft skills like communication, creativity and critical thinking if they are to flourish in the labor market (2). The third is that The report predicts three classes of work in the world of 2030. Changing jobs – those that exist now but which have evolved beyond their current form, sometimes radically, through the integration of technology, and Fading jobs – those replaced by intelligent machines. (3) Finally, Tomorrow’s Jobs. When The Future Laboratory teamed up with Microsoft to bring some clarity for career planners they produced Tomorrow’s Jobs, a report that predicts some of the more important IT-related jobs of the future. The Future Factory used a method that all of us can use to good effect. First you look at the patterns coming forward from the past ten or twenty years, and then make predictions by projecting the same patterns into the future. This is how to be proactive about seeing where the world is heading. (5)

In William, Halal, Kolber Jonathan, and Davies Owen’s views,“Forecasts of AI and Future Jobs in 2030: Muddling Through Likely, with Two Alternative Scenarios”(Walliam,2016). The purpose is that Artificial Intelligence will be coming most people sill lose job because Ai replace people’s work most behavior will auto machine. we do not need labor power. After decades of failed promises, artificial intelligence (AI) is now taking off. Yesterday’s doubters have been silenced, and the only current debate is about how deep and how fast intelligent machines will automate jobs, and whether the same technological forces will generate enough new work. Several forecasts suggest AI is likely to eliminate almost half of present jobs by 2025, resulting in massive unemployment (Rutkin, 2013). Ray Kurzweil, now at Google, extrapolates the growth of computer power to estimate that a US$1000 PC will match the human brain about 2020, and powerful AI systems will soon follow (Frey, 2016). Ben Goertzel, leader of the OpenCog project said “I am confident that we will have human-level AI by 2025. Maybe sooner” (Olson, 2013, p.1). Fears of mass unemployment by automation have been a constant throughout industrialization, but they are seldom realized. The evidence shows that automation reduces costs and frees up labor, which allows further economic growth and new jobs in areas of demand that were unexpected. Today’s fears that AI will eliminate masses of jobs does not recognize how this dynamic will play out in the new economy that is emerging. They are somewhat reminiscent of the Y2K crisis that never materialized (5).

By Steve writes, “New Tools Needed to Track Technology’s Impact on Jobs, Panel Says” (Steve,2017). The purpose is that America needs new tools for the timely measurement and monitoring of technology, jobs and skills to cope with the advance of artificial intelligence and automation. Both the report and commentary were spurred by the advances in A.I. in recent years, including document-reading software and self-driving cars, which promise to make inroads into work done by humans. That prospect has created angst for many American workers about the difficulties of adapting to technological change and the failure of institutions to help them (2). New Tools Needed to Track Technology’s Impact on Jobs, Panel Says - The New York Times Those moves could eventually give a worker in a declining occupation useful information about a more promising occupation, with some similar skills but also requiring some new ones, Mr. Mitchell said. Then the software tool might also pull information on job placement rates for courses that teach those new skills (3).

In the Mitchell article said “the software tool might also pull information on job placement rates for courses that teach those new skills” (3). In the artificial intelligence has more area, software tool can help our life. Let us life get convenience and we save more time for doing some traditional events. In my I say section, I want t o talk about software tool in the artificial intelligence area.

Work cited

Jerry, Kaplan. Viewpoint Arti cial Intelligence: Think Again. 2017th ed., vol. 60, 2017, pp. 1-4, 1 vols.

Itamar, Arel, Rose Derek, and Karnowski Thomas. Deep Machine Learning—A New Frontier in Artificial Intelligence Research Research Frontier. The University of Tennessee, USA, 2010, pp. 1-6.

David, Tuffey. CAN INTELLIGENT MACHINES IN THE WORKFORCE LEAD TO A NET GAIN IN THE NUMBER OF JOBS? 2016th ed., Griffth University, pp. 1-7.

William, Halal, Kolber Jonathan, and Davies Owen. Forecasts of AI and Future Jobs in 2030: Muddling Through Likely, with Two Alternative Scenarios. 2016th ed., vol. 10, 2016, pp. 83-96.

STEVE, LOHR. New Tools Needed to Track Technology’s Impact on Jobs, Panel Says. 2017th ed., New York Times, NewYork, pp. 1-4.